Analysis of Activity Measurement for Accurate Oestrus Detection in Dairy Cattle

Errors in oestrus detection prevent many dairy farms from attaining their reproduction goals. A data base of animal activity sampled at 1-min intervals has been collected with electronic pedometers and correlated with other indications of oestrus. These data indicate that an activity-based decision...

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Bibliographic Details
Published inJournal of agricultural engineering research Vol. 58; no. 2-3; pp. 107 - 114
Main Authors Koelsch, R.K., Aneshansley, D.J., Butler, W.R.
Format Journal Article
LanguageEnglish
Published London Elsevier Science Ltd 01.06.1994
Academic Press
Subjects
Animal productions
Biological and medical sciences
Fundamental and applied biological sciences. Psychology
Terrestrial animal productions
Vertebrates
Methodology
Ruminant animal
Dairy cattle
Ox
Sexual reproduction
Accuracy
Electronic pedometer
Ungulata
Hormone
Electronic equipment
Farming animal
Biochemical analysis
Estrus
Bovine
Instruments
Dairy farming
Cow
Biological activity
Vertebrata
Mammalia
Animal activity
Artiodactyla
Measurement method
Detection
LH
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Summary:Errors in oestrus detection prevent many dairy farms from attaining their reproduction goals. A data base of animal activity sampled at 1-min intervals has been collected with electronic pedometers and correlated with other indications of oestrus. These data indicate that an activity-based decision of oestrus first occurs in close proximity to the pre-ovulatory surge of luteinizing hormone. The data base is also used to evaluate various comparison procedures for distinguishing between oestrus and dioestrus states. Three newly developed comparison procedures improve the accuracy of activity-based decisions for identifying oestrus and dioestrus periods when compared with commonly referenced procedures in the literature. The new methods (1) compare the current and past activity statistically as two independent treatments, (2) identify oestrus based upon both duration of an elevated activity and increased activity intensity, and (3) replace the averaging function with other digital signal processing techniques. Decisions based upon these procedures correctly identified approximately 70% of the periods of oestrus while accurately classifying 99% of the dioestrus periods.
ISSN:0021-8634
1095-9246
DOI:10.1006/jaer.1994.1040